Aapryl Skill Screening Module Product Description & User Guide

 

Overview

Aapryl’s Skill Screening module is designed to streamline the process of identifying top investment managers. By combining proprietary skill-based analytics with flexible multi-dimensional filtering, the module enables investment professionals to efficiently narrow large manager universes down to high-probability outperformers.

 

Aapryl Score

The proprietary measure of a manager’s skill, measured by the likelihood they finish in the top quartile of an Aapryl peer group over the next 36 months. A score of 5, would be the lowest likelihood of a product being in the top quartile, and a score of 1 would be the highest likelihood based on Aapryl’s proprietary methodologies

 

The module supports managers across multiple product types — Mutual Funds, Separate Accounts (SMAs), and ETFs — and covers equity and fixed income strategies globally. Data powering the screens comes from both third-party providers and Aapryl’s own proprietary calculations.

 

Learning Goals

• Understand the basics of Aapryl’s Screening module
• Use the Screening module to increase the probability of choosing managers who will outperform
• Understand the data points available to both view and screen managers

 

Step 1: Primary Filters

Users begin by defining the investment universe using the primary filter bar at the top of the Screening module. These filters determine which managers appear in the results table.

 

Primary Filter Options
Custom Universe / List	Select or create a proprietary manager list or peer group
Product Type	Mutual Funds, Separate Accounts (SMAs), or ETFs
Market Cap	Small, Medium, or Large Cap (sourced from 3rd-party data providers)
Regional Focus	US, Global ex-US, Global, or Emerging Markets
Aapryl Peer Group	Proprietary classifications: Relative/High Quality Value, Cyclical/Low Quality Value, High Quality/Stable Growth, Cyclical/High Growth, Defensive, Garp Blend
Portfolio Strategy	Filter by the manager’s stated investment approach

 

Step 2: Results Table

Once primary filters are applied, the results table auto-populates with all matching managers. The table is fully customizable — users can add or remove columns to surface the data points most relevant to their mandate.

 

• Click any column header in the black heading bar to sort ascending or descending
• Select managers using checkboxes to queue them for deeper analysis
• Aapryl Probability is displayed by default and is the primary outperformance signal

 

Available Data Fields (50+ Columns)

The following categories of data are available to add to the results table:

 

Data Field Categories
Aapryl Proprietary	Aapryl Probability, Aapryl Opportunity Score, Aapryl Manager Skill Score, Edge Score (Factor Timing), Consistency Score (Factor Timing), Edge Score (Stock Selection), Consistency Score (Stock Selection)
Factor Exposures (9)	Value, Core, Growth, Defensive, Economic Sensitivity, Momentum, Quality, Yield, Low Volatility
Fund Characteristics	AUM, Inception Date, Fees, No. of Long Holdings, Data Source
Performance	Manager 12-Month Return, Benchmark 12-Month Return
Benchmarks	Default Benchmark, Aapryl Peer Group Benchmark
Ownership / Diversity	% Minority Owned, % Women Owned, % Hispanic, % Asian, % African American, % Native American, % Disabled, % Veteran
Classification	Regional Focus, Portfolio Management Strategy, Market Cap Size, Aapryl Peer Group

 

Step 3: Secondary Filters

After reviewing the results table, users can apply secondary filters to narrow results further. Any field that has been added to the results table becomes available as a secondary filter criterion.

 

• Secondary filters support the following operators:
• Greater than (>)
• Greater than or equal to (>=)
• Less than or equal to (<=)

 

Example Filter Combinations

Use Case Examples
Top-Quartile Outperformers	Aapryl Probability > 60% AND Edge Score > 1.0
Diversity Mandates	% Minority Owned > 0 AND % Women Owned > 10%
Concentrated Managers	No. of Long Holdings < 100
Minimum AUM Threshold	AUM >= $500M
Experienced Track Records	Inception Date <= 01/01/2010

 

Step 4: Run Analysis

After using filters to build a shortlist, users select managers and proceed to deeper analytical tools using the action buttons on the right side of the interface.

 

Action Buttons
Run Analysis	Launches the full Aapryl analytics dashboard for selected managers, including style decomposition and skill attribution
Run Style Analysis	Generates style-focused decomposition showing factor exposures over time
Save Report	Exports and saves the current screening results for later reference or sharing
Next	Advances to the next step in the manager evaluation workflow

 

Fixed Income Skill Screening

Aapryl offers a parallel Skill Screening module specifically designed for fixed income managers. The workflow mirrors the equity module but is optimized for bond strategies, with an expanded set of FI-specific data fields.

 

Fixed Income-Specific Primary Filters

• Custom Universe, Product Type, Portfolio Strategy, Aapryl Categories (FI-specific)
• Target universes include: Core Investment Grade, Credit Intermediate, EM Hard Currency, and more

 

Fixed Income Data Fields

In addition to standard performance and ownership fields, the FI module includes 29 sector exposure columns:

 

Fixed Income Sector Exposures
Rates / Govt	US TIPs, Treasuries (Short/Intermediate/Long/T-Bills), Agency MBS, Non-US Supra-Govt, Gov & Agency
Credit	US Corp (Short/Intermediate/Long), HY (Short/Intermediate/Long), Credit (Short/Intermediate/Long), Bank Loans
Municipal	Muni (Ultra Short, Short, Intermediate, Long, High Yield)
Asset Backed	Asset Backed Securities
International	Non-US Sovereign, EM Sovereign, EM Core, EM HY, EM Hard Currency, EM Local, Global HY, International TIPs/Core/Corp
Risk Attributes	Duration, Credit Quality, 30-Day Yield, 12-Month Yield, Expected Alpha, Market Cycle Placement

 

Fixed Income Screening Use Cases

• Core mandate: Filter Core Investment Grade + Probability >60% + Duration 4-6
• Tax-exempt: Muni Intermediate + Consistency Score >0.8
• Satellite allocation: Credit Long + Expected Alpha >1.5%
• Save frequently-used FI universes as Custom Universe templates for recurring screens

 

Key Insights & Best Practices

 

Equity Screening

• Aapryl Probability above 70% identifies managers with high odds of top-quartile performance over 3 years
• Edge Score dominance in Stock Selection vs. Factor Timing reveals whether alpha comes from security picks or style rotations
• Long inception dates with low fees balance experience against cost drag
• Market Cycle Placement shows which economic phases favor each manager

 

Fixed Income Screening

• Agency MBS + Treasuries Intermediate dominance signals a liquidity focus
• EM HY + Bank Loans tilts indicate yield-seeking strategies
• Edge Score superiority in Security Selection over Factor Timing identifies strong credit pickers vs. duration timers
• High Aapryl Probability (>70%) combined with ownership diversity metrics supports dual mandates

 

The Aapryl Skill Screening Module Define universe → Customize columns → Apply secondary filters → Run Analysis

 

For more information, visit www.aapryl.com